QPSK

利用matlab强大的功能，可以画出中国国旗的一个小程序！(Using matlab powerful features, you can draw the flag of a small program in China!)

说明：  利用lindoapi借口在matlab中调用lindoapi中的函数，构造混合整数规模模型，求解小规模TSP问题的最优解(lindoapi excuse the use of Matlab lindoapi call the function, Mixed Integer scale tectonic model for small-scale TSP Optimal Solutions)

说明：  标准粒子群算法的matlab源程序 可以直接运行(Standard particle swarm algorithm matlab source code can be run directly)

基于暗原色去雾的图像代码，用了软抠图和另两种改进算法，附加txt说明文档(Based on dark colors to fog image code, with a soft matting, and another two improved algorithms, additional documentation txt)

Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models.

包括刘金琨编著的《先进PID控制与matlab仿真》，《智能控制》，《滑模变结构控制Matlab仿真》三本书的源代码，适合于学习或研究PID控制、智能控制和滑模控制。(Including matlab source code of three books writeen by Liu Jinkun. 1. Advanced PID control and matlab simulation 2. Intelligent Control 3. Sliding Mode Control and matlab simulation )

整数优化工具箱,可解决混合优化，整数优化等(optimization forum)

小波变换及其MATLAB工具的应用，这个供大家学习研究用(Wavelet Transform and Its Application of MATLAB tools, for them to learn from this study)

用OpenCV实现的Matlab中形态学细化、提取骨架、收缩算法。测试效果与Matlab相同。(Algorithms of morphological thinning,Skeleton and Shrink,ported from Matlab to OpenCV.)

潮汐调和分析关于无潮点及潮流方向与潮时的计算与分析。(Tidal wave of harmonic analysis on non-point and the trend direction and tide calculations and analysis.)